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dc.contributor.authorFan, TFen_US
dc.contributor.authorLiu, DRen_US
dc.contributor.authorLiau, CJen_US
dc.date.accessioned2014-12-08T15:25:09Z-
dc.date.available2014-12-08T15:25:09Z-
dc.date.issued2005en_US
dc.identifier.isbn3-540-26257-1en_US
dc.identifier.issn1860-949Xen_US
dc.identifier.urihttp://hdl.handle.net/11536/17544-
dc.description.abstractData mining is an instance of the inductive methodology. Many philosophical considerations for induction can also be carried out for data mining. In particular, the justification of induction has been a long-standing problem in epistemology. This article is a recast of the problem in the context of data mining. We formulate the problem precisely in the rough set-based decision logic and discuss its implications for the research of data mining.en_US
dc.language.isoen_USen_US
dc.titleJustification and hypothesis selection in data miningen_US
dc.typeProceedings Paperen_US
dc.identifier.journalFoundations of Data Mining and Knowledge Discoveryen_US
dc.citation.volume6en_US
dc.citation.spage119en_US
dc.citation.epage130en_US
dc.contributor.department資訊管理與財務金融系 註:原資管所+財金所zh_TW
dc.contributor.departmentDepartment of Information Management and Financeen_US
dc.identifier.wosnumberWOS:000232911000007-
Appears in Collections:Conferences Paper